Uncertain Machine Ethical Decisions Using Hypothetical Retrospection
This work addresses ethical decision-making in autonomous systems, offering a flexible approach that could improve explainability, though it appears incremental as it builds on existing philosophical arguments.
The authors tackled the problem of machine ethical reasoning under uncertainty by proposing a hypothetical retrospection argumentation procedure, resulting in a versatile framework that integrates multiple philosophical theories and enhances transparency for human resonance.
We propose the use of the hypothetical retrospection argumentation procedure, developed by Sven Ove Hansson to improve existing approaches to machine ethical reasoning by accounting for probability and uncertainty from a position of Philosophy that resonates with humans. Actions are represented with a branching set of potential outcomes, each with a state, utility, and either a numeric or poetic probability estimate. Actions are chosen based on comparisons between sets of arguments favouring actions from the perspective of their branches, even those branches that led to an undesirable outcome. This use of arguments allows a variety of philosophical theories for ethical reasoning to be used, potentially in flexible combination with each other. We implement the procedure, applying consequentialist and deontological ethical theories, independently and concurrently, to an autonomous library system use case. We introduce a preliminary framework that seems to meet the varied requirements of a machine ethics system: versatility under multiple theories and a resonance with humans that enables transparency and explainability.